DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.
Methods Mol Biol
; 2809: 237-244, 2024.
Article
em En
| MEDLINE
| ID: mdl-38907901
ABSTRACT
Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformatics prediction for tumor neoantigens has rapidly developed, focusing on the prediction of peptide-HLA binding affinity. In this chapter, we introduce a user-friendly tool named DeepHLApan, which utilizes deep learning techniques to predict neoantigens by considering both peptide-HLA binding affinity and immunogenicity. We provide the application of DeepHLApan, along with the source code, docker version, and web-server. These resources are freely available at https//github.com/zjupgx/deephlapan and http//pgx.zju.edu.cn/deephlapan/ .
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Peptídeos
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Software
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Biologia Computacional
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Aprendizado Profundo
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Antígenos HLA
Limite:
Humans
Idioma:
En
Revista:
Methods Mol Biol
Ano de publicação:
2024
Tipo de documento:
Article